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MFC-027 BeitelSchiereck.doc

  1. 1. Value creation of investment bank participation in the German M&A-Business Derick Beitela and Dirk Schiereckb Working paper November, 9th 2003 Abstract Although the recent downturn in M&A-activity, over the last 10 years, the M&A-market in Germany showed a sharp increase in terms of transaction volume and number of deals. Along with a growing market, investment banks play a more and more important role in the German M&A-market. Investment bank participation in Germany has not been studied in much detail. This study investigates the role investment banks play in creating value in M&A-transaction of German acquirers. We find, that investment bank participation as well as reputation does have a very limited impact on value creation. Key words: Investment banks, investment banking, Mergers & Acquisitions, German M&A-market JEL classification: G24, G34 a Derick Beitel is research assistant at the Institute for Mergers & Acquisitions at the University of Witten/Herdecke. E-mail address: derick.beitel@web.de b Dirk Schiereck is professor at the Endowned Chair of Banking and Finance at the European Business School in Oestrich-Winkel. E-mail address: dirk.schiereck@ebs.de Value creation of investment bank participation in the German M&A-Business
  2. 2. 1. Introduction Over the last 15 years, the M&A-activity in Germany showed a sharp increase in terms of transaction volume and number of deals.1 Although traditionally the vast majority of trans- actions in Germany have been done without external M&A-advisors, investment banks are becoming more and more important in the German M&A business.2 Advisory services of investment banks can be viewed as capital investments. As an example, Saunders and Srinivasan (2001) show (on the basis of 611 US M&A transactions between 1985 and 1998) an average fee-payment of USD 4 m. Mandating an investment bank therefore only makes sense if a company gains an advantage that the firm could not achieve without the advisory services Empirical studies focusing on the role of investment banks in M&A transactions are rare. Almost all existing studies focus on the US-market. The role of investment bank participation in the German M&A-business has not been studied in much detail. Because of the relatively immature M&A-market in Germany and structural differences between the US and Germany (e.g. in corporate ownership and control) we take a deeper look at the German M&A-market. Value creation of investment bank participation can be measured in different ways. Referring to the existing body of empirical studies in this field, this paper concentrates on the following research questions: 1. Do shareholders of German buyers gain if their management uses an investment bank? 2. Are there a differences in the purchase prices if German buyers use external M&A- advise? 3. Do shareholders benefit from investment bank participation in the mid-term? Besides the shareholder wealth effects and purchase prices, this paper analyzes whether transactions advised by investment banks are completed in a shorter period of time compared to those without external M&A-advisors. The fourth research question is: 4. Does investment bank participation has an influence on the duration between the announcement and the time a transaction is completed (time to completion)? 1 According to Thomson Financial SDC, the average CAGR of the transaction volume in Germany between 1990 and 2001 was 17%. 2 This goes along with the increased presence of investment banks in Germany over the last decade. 2
  3. 3. Besides investment bank participation, we also explore potential differences in the “quality” of investment banks used, measured by reputation. The structure of this paper includes a short review of the literature followed by a description of the data and methodology used. After presenting the results of the study, the paper ends with a conclusion. 2. Review of the literature There is mixed evidence on the shareholder wealth effects of investment banks acting as M&A-advisors.3 For acquiring firms, Servaes and Zenner (1996) find no impact of investment banks on the returns earned by the acquiring firms’ shareholders. Allen et al. (2001), who compare transactions advised by commercial banks against those advised by investment banks show, that returns are higher for acquirers that employ no advisor at all. Looking at the reputation of investment banks, Bowers and Miller (1990), Servaes and Zenner (1996), Kale et al. (1998), Rau (2000), Hunter and Jagtiani (2000) or Rau and Rodgers (2002) come to a similar conclusion: First-tier investment banks are not better in providing superior shareholder wealth effects compared to lower tier investment banks. Concentrating on target firm shareholders, Kale et al. (1998) find, that cumulative abnormal returns are lower if only the target firm chooses external M&A-advise. In contrast, target firm shareholders benefit, if either the bidder or the target firm is advised by a first-tier compared to a lower-tier investment bank. Bowers and Miller (1990) show similar results. Hunter and Walker (1990) compare combined abnormal Dollar-returns against combined fee payments. They show an average cumulated abnormal Dollar-return of USD 85m versus a combined average fee payment of USD 5m. Bowers and Miller (1990) who concentrate on first- versus lower-tier investment banks find, that combined wealth effects are higher, if the target, the bidder or both are advised by a high quality investment bank. Kale et al. (1998) come to similar conclusions. Investigating the premiums paid by acquiring firms, Hunter and Walker (1990) find no impact of investment bank participation. Instead, acquirers pay higher premiums, if the cash/asset- ratio of target firms are high. Concentrating on the reputation of investment banks, Michel et al. (1991), McLaughlin (1992) or Rau (2000) show, that acquiring firms pay a higher premium if they are advised by a first-tier M&A-advisor. In the transaction sample of Rau (2000), acquirers with first-tier investment banks pay an acquisition premium (median) of 3 For a detailed summary of the current empirical literature on the role of investment banks in mergers and acquisitions, see Beitel and Schiereck (2004a). 3
  4. 4. 56,3%. The premium paid by acquirers with third-tier banks equals 38,1%. McLaughlin (1990), McLaughlin (1992), Kesner et al. (1994), McLaughlin (1996), Rau (2000) or Saunders and Srinivasan (2001) analyse fee payments. The results convey a positive correlation between the absolute amount of fee payments and transaction volumes. On average, dependent on the transaction type, up to 70% of fee payments are paid as contingent fees. Saunders and Srinivasan (2001) show, that first-tier investment banks earn higher (absolute) fee payments compared to lower-tier banks. However, the average transaction volume advised by first-tier investment banks is also higher. Investigating the relationship between fee payments and shareholder wealth effects, McLaughlin (1992) finds, that higher fee payments are not related to higher acquisition returns of acquiring firms’ shareholders. 3. Value creation of investment bank participation in the German M&A-Business 3.1 The data The transaction sample includes 398 M&A-transactions of German buyers between January 1995 until December 2001.4 The sample is drawn from the Securities Data Corporation (SDC) database and has been completed by transaction published in the Computasoft M&A and the Bloomberg databases. Capital market information (e.g. market capitalization of the trans- action partners) is taken from Thomson Financial Datastream. Firm specific data is drawn from the transaction databases used as well as from the Markus and Amadeus databases or directly from annual reports.5 The criteria for choosing a transaction are: • the announcement day is between January 1st, 1995 and December 31st,, 2001, • the status of the transaction is completed, • the transaction volume is at least 25 Mio. EUR, • the home country of the acquirer is Germany, • the transaction includes a change of control (i.e. before the announcement of the trans- action the buyer owns less and after completion of the transaction more than 50% of the shares/assets of the target), • the business focus of the transaction partners is not mainly in the financial services industry nor in the real estate business. On the basis of these criteria we built two samples: 1) Transactions of German buyers with investment banks („IB-sample“) and 2) Transactions of German buyers without investment 4 We analyze German acquirers only because for targets relevant data is often unknown. 5 Because of limitation in data (e.g. financials of non-quoted targets are often unknown) we always indicate the number („N“) of parameters analyzed. 4
  5. 5. banks („Non-IB-sample“). The IB-sample comprises 172 transactions, the Non-IB-sample 226 transactions. In order to reflect the minimum transaction volume demanded by most of the investment banks analyzed, we only considered transactions with a minimum transaction value (rank value) of EUR 25 m.6 Restrictions on the business focus were done to increase the comparability of the transactions analyzed. Table 1 shows the time structure and the transaction volume of the M&A transactions analyzed. Table 1: Time structure and transaction volume of data sample IB-sample Non-IB-sample Year Number of in % Average transaction volume Year Number of in % Average transaction volume transactions (in EURm) transactions (in EURm) 2001 25 14,5% 1.330,98 2001 31 13,7% 111,76 2000 53 30,8% 1.843,44 2000 56 24,8% 225,95 1999 42 24,4% 2.388,57 1999 40 17,7% 206,38 1998 21 12,2% 2.168,64 1998 37 16,4% 289,06 1997 11 6,4% 1.222,04 1997 23 10,2% 162,91 1996 14 8,1% 601,76 1996 23 10,2% 186,22 1995 6 3,5% 1.070,34 1995 16 7,1% 163,56 Total 172 100% 1.777,57 Total 226 100% 202,28 Source: Thomson Financial SDC, Computasoft M&A-Data and Bloomberg. The average transaction size in the IB-sample is approximately 8.8 times higher than in the Non-IB-sample. In 80% of the transactions, German buyers with investment banks, acquire targets outside of Germany. The percentage of cross border transactions amounts to 65% in the Non-IB-sample.7 To be able to analyze abnormal returns gained by the shareholders involved, only quoted companies can be examined. Out of the 172 transactions in the IB-sample, there are 142 quoted buyers and 60 quoted targets. In the Non-IB-sample, 145 buyers and 28 targets are publicly listed. To explore the impact of investment bank reputation, we further classify our IB-sample into two different sub-samples.8 We classify an investment bank as one with “high reputation”, if the advisor was among the top-five investment banks, in terms of advised 6 For more details on minimum transaction volumes, see Lüdke and Frien (2001). 7 Further analyses on the transaction parameters and its impact on the decision of German buyers to use investment banks can be found in Beitel and Schiereck (2004b). 8 Reputation of investment banks is often used as a proxy-variable for the quality of its advisory services. Empirical (M&A-focused) studies, investigating investment banks by its reputation can be found in Bowers and Miller (1990), McLaughlin (1990), Michel et al. (1991), McLaughlin (1992), Servaes and Zenner (1996), Kale et al. (1998), Rau (2000), Hunter and Jagtiani (2000), Saunders and Srinivasan (2001), Schiereck and Unverhau (2002) or Rau and Rodgers (2002). 5
  6. 6. (cumulative) transaction volume in the two years preceding the transaction analyzed. 9 As we analyze German buyers acquiring mainly European targets, we use European league tables to classify our sample. Table 2 shows all investment banks who have been among the top-ten M&A-advisors in Europe between 1993 and 2001. No investment bank has been consistently among the top-5 M&A-advisors over the complete period analyzed. Morgan Stanley (6-times), UBS Warburg (6-times), Lazard (4-times), JP Morgan (3-times) and Goldman Sachs (3-times) were among the top-five banks the most often. 47 German buyers (27%) have been advised by investment banks with high reputation. Table 2: Top-10 investment banks in European M&A-transactions between 1993 and 2001 Investment bank Year / Ranking 1993 1994 1995 1996 1997 1998 1999 2000 2001 Goldman Sachs 10 10 6 6 4 2 1 1 1 JP Morgan 8 6 1 3 6 3 4 4 2 Morgan Stanley 7 4 2 2 1 1 3 2 3 Merrill Lynch >10 9 >10 >10 >10 7 2 9 4 Dresdner Kleinwort Wasserstein 2 >10 >10 >10 7 >10 10 10 5 Salomon Smith Barney 5 5 7 7 8 6 >10 3 6 ING Barings >10 7 5 10 >10 >10 >10 >10 7 Lazard 4 2 4 4 3 9 9 7 8 UBS Warburg 1 1 3 1 2 5 5 6 9 Credit Suisse First Boston >10 3 8 8 5 4 8 5 10 Rothschild 9 >10 10 9 9 8 6 8 >10 Societe General 6 >10 >10 >10 >10 >10 >10 >10 >10 Deutsche Bank 3 8 9 >10 10 >10 7 >10 >10 BNP Paribas >10 >10 >10 5 >10 10 >10 >10 >10 Source: Thomson Financial SDC. 3.2 Methodology In order to address the four different research questions described above, we analyze the (short-term) cumulative abnormal returns (CARs), the purchase prices and the mid-term 9 If a buyer has been advised by more than one investment bank, we use (in conjunction with McLaughlin (1992) and Rau (2000)) the reputation of the bank with the highest reputation. see McLaughlin (1992), p. 239 or Rau (2000), p. 303. 6
  7. 7. acquisition performance of German buyers. In addition we look at the duration between transaction announcements and completions (time to completion). The methodology used for measuring CARs builds on the event study methodology (OLS market model) as introduced by Brown and Warner (1980), Dodd and Warner (1983) and Brown and Warner (1985). Referring to the existing literature, we consider several event windows around the announcement day in intervals of -20 to +20 trading days.10 To calculate the market model regression parameters, we use a clean period of -301 to -21 trading days. 11 For acquirers and targets who were not publicly traded over the complete clean period, estimates for the regression parameters are done with the corresponding period of time.12 For German buyers and targets, we used the Morgan Stanley Dean Witter MSCI Standard Market Index for Germany. For foreign targets, the corresponding MSCI country index was used. Actual returns were calculated on the basis of the „total return index“ as computed by Thomson Financial Datastream for each trading day.13 To compare the different transaction samples described above, univariate comparisons are made between the IB- and the Non-IB-sample as well as between the samples with investment banks of different reputation. Because the precondition of normal distributed data is not always met, we use non-parametric (Mann-Whitney rang sum tests) as well as parametric tests (t-tests). Similar methodology is used by Servaes and Zenner (1996) or Rau (2000). 14 To control for other variables influencing value creation in M&A-transactions, we also ran multivariate OLS-regressions. As proxies for purchase prices, we looked at acquisition premiums and transaction multiples, as described in table 3. Table 3: Acquisition premiums and transaction multiples Acquisition premiums Description CAR ( Z ) i • CAR(Z)i = cumulative abnormal returns of the target i over the event window 10 If the announcement day falls on a weekend or holiday, we use the first trading day after the announcement day. 11 This period is consistent with the one used by Bowers and Miller (1990). Hunter and Walker (1990), Kale et al. (1998), Saunders and Srinivasan (2001) and Schiereck and Unverhau (2002) use a similar period. McLaughlin (1992), Servaes and Zenner (1996), Rau (2000), Allen et al. (2001) or Rau and Rodgers (2002) use a slightly shorter period of time. 12 17 acquirers in the IB- and 18 acquirers in the Non-IB-sample are not quoted over the complete clean period. The average clean period of these companies is 179 trading days in the IB- and 171 trading days in the Non-IB-sample. 13 The advantage of using the total return index is, that several adjustments (e.g. for dividend payments) are already included. 14 See Servaes and Zenner (1996), p. 798 respectively Rau (2000), p. 305. 7
  8. 8. TAVol i • TAVoli = transaction volume (100% of acquired shares) • TotAssi = Total assets of target i, as shown in the last annual TotAss i statement prior to the announcement of the transaction Transaction multiples Description TAVol • TAVol = transaction volume (for 100% of the acquired shares) • Salesi = Sales of target i as shown in the last annual statement prior to Salesi the announcement of the transaction TAVol • EBITDAi = Earnings before interest, tax, depreciation and amortization of target i , referring to the last annual statement prior to EBITDAi the announcement of the transaction The method for measuring mid-term acquisition performance builds on the adjusted abnormal stock return of the acquiring company over a period of 125 trading day as well as 250 trading days. To compute abnormal returns, we compare actual stock returns against the performance of the corresponding market indices. The mid-term acquisition performance is then calculated in analogy to the market model used to calculate (short-term) CARs.15 3.3 Results Table 4 shows the CARs of German buyers in the IB- and Non-IB-sample over different event windows. CARs of the acquirers in the IB-sample, as well as in the Non-IB-sample are not significantly different from zero. The percentage of transactions with positive CARs is similar in both samples and varies around 50%. CARs of German buyers with and without investment banks are not significantly different. German acquirers do not earn higher or lower CARs is they are advised by investment banks. The results in table 4 confirm the results obtained in earlier (US-focused) studies: Investment bank participation in M&A-transactions does neither have a significant positive nor negative effect on CARs earned by shareholders of acquiring companies. Table 4: CARs of German buyers with and without investment banks IB-sample Non-IB-sample Event window CAR p-value TA w/ CAR p-value TA w/ Difference t-test CAR>0 CAR>0 CAR p-value 15 Referring to Rau and Rodgers (2002) we only analyzed transactions, where the transaction volume is at least 10% of the market capitalization of the buyer (20 trading days before the announcement of the transaction). 8
  9. 9. (IB-sample: N=142, Non-IB-sample: N=145) [-20;0] 1,61 0,441 53,5 0,92 0,468 52,4 0,69 0,352 [-10;0] 1,37 0,431 49,3 0,89 0,457 49,7 0,48 0,352 [-3;0] 0,57 0,452 51,4 1,47 0,384 55,9 -0,90 0,128 [0] 0,08 0,486 50,7 0,34 0,446 55,2 -0,26 0,287 [-1;+1] 0,93 0,410 57,7 0,83 0,423 55,9 0,10 0,352 [-3;+3] 0,23 0,485 52,8 1,03 0,438 51,0 -0,80 0,213 [-10;+10] 0,71 0,474 52,8 -0,40 0,514 45,5 1,11 0,248 [-20;+20] 0,23 0,494 52,8 -1,36 0,534 44,1 1,59 0,247 Besides CARs of German buyers, we also looked at the combined cumulative abnormal returns. In six out of eight event windows analyzed, the combined CARs in the IB-sample are lower as those in the Non-IB-sample. In no case, they are significantly lower. Table 5 shows the results. Table 5: Combined CARs with and without investment banks advising German buyers IB-sample Non-IB-sample Event- CAR Media TA w/ CAR Median TA w/ Difference t-test MWU window n CAR>0 CAR>0 medians p-value p-value (IB-sample: N=47; Non-IB-sample: N=18) [-20;0] 3,96 3,53 63,8 6,11 2,87 72,2 0,66 0,250 0,289 [-10;0] 3,75 2,08 66,0 4,44 3,59 66,7 -0,41 0,403 0,391 [-3;0] 2,32 1,10 55,3 4,10 2,24 66,7 -2,03 0,215 0,178 [0] 1,66 0,51 59,6 2,10 0,68 66,7 -1,59 0,403 0,459 [-1;+1] 2,95 1,92 66,0 2,06 2,42 72,2 -0,14 0,493 0,489 [-3;+3] 1,90 0,62 53,2 3,13 3,28 72,2 -2,51 0,310 0,206 [-10;+10] 2,41 2,80 61,7 2,49 3,76 72,2 0,31 0,491 0,294 [-20;+20] 1,86 1,13 51,1 4,83 6,22 72,2 -3,70 0,257 0,219 Besides pure investment bank participation German buyers might benefit if they receive advise by investment banks with high reputation. Table 6 summarizes the results. Table 6: CARs of German buyers with investment banks with different reputation and combined CAR with investment banks with different reputation advising German buyers IB with high reputation IB with low reputation Event CAR Media TA w/ CAR Median TA w/ Differenc t-test MWU window n CAR>0 CAR>0 e medians p-value p-value 9
  10. 10. A. CAR German buyers (IB w/ high reputation: N=41; IB w/ low reputation: N=101) [-20;0] -0,30 -1,82 41,5 2,38 1,82 58,4 -3,64** 0,227 0,033 [-10;0] 0,17 -1,77 41,5 1,86 0,41 52,5 -2,18* 0,233 0,089 [-3;0] -0,23 -0,80 43,9 0,90 0,47 54,5 -1,27 0,204 0,147 [0] 0,34 0,23 56,1 -0,02 0,00 48,5 0,23 0,340 0,494 [-1;+1] 0,32 0,25 58,5 1,18 1,14 57,4 -0,89 0,419 0,371 [-3;+3] -0,95 -0,76 46,3 0,71 0,53 55,4 -1,29* 0,154 0,088 [-10;+10] -0,52 -0,35 46,3 1,20 1,33 55,4 -1,68 0,273 0,242 [-20;+20] -1,11 -2,78 39,0 0,77 2,47 58,4 -5,25 0,320 0,182 B. Combined CAR (IB w/ high reputation: N=20; IB w/ low reputation: N=27) [-20;0] 3,75 2,78 65,0 4,12 3,68 63,0 -0,90 0,470 0,366 [-10;0] 5,97 4,13 70,0 2,11 1,05 63,0 3,08 0,099 0,253 [-3;0] 4,03 0,73 50,0 1,06 1,10 59,3 -0,37 0,095 0,296 [0] 2,50 0,39 55,0 1,04 0,51 63,0 -0,12 0,022 0,350 [-1;+1] 4,54 3,51 80,0 1,78 0,67 55,6 2,84** 0,040 0,022 [-3;+3] 3,78 1,96 65,0 0,52 -0,18 44,4 2,14 0,103 0,172 [-10;+10] 6,92 6,34 65,0 -0,94 2,37 59,3 3,97** 0,015 0,041 [-20;+20] 4,66 4,54 55,0 -0,22 -1,67 48,1 6,21 0,152 0,145 * = significant at the 10%-level, ** = significant at the 5%-level. CARs of German buyers are in seven out of eight event windows smaller, if the acquirers are advised by high reputation investment banks. In three event windows ([-20;0], [-10;0] and [-3;+3]) the difference is significant according to the relevant Mann-Whitney-tests. Also we find differences in combined CARs. The combined CARs in the sample with investment banks with high reputation are significantly higher in the [-1;+1] and [-10;+10] event windows compared to the sample with investment banks with low reputation. Similar to the studies made by Kale et al. (1998), Bowers and Miller (1990) or Hunter and Walker (1990) the results show, that transactions advised by investment banks with high reputation show higher combined CARs. Although this result is interesting from a macro economic point of view, German acquirers – as shown above – do not benefit from these advisory services.16 As described above we also looked at acquisition premiums and transaction muliples as proxies for purchase prices. Table 7 summarizes the premiums and multiples paid by German acquirers with and without investment banks. Table 7: Acquisition premiums and transaction multiples paid by German buyers with and without investment banks IB-sample Non-IB-sample Average Median (N) Average Median (N) Difference t-test MWU medians p-value p-value 16 Comparing CARs of German buyers with high reputation investment banks with those obtained by German buyers without extern advise, we find that in six out of eight event periods, the CARs are lower in the high reputation investment bank sample (not shown). In contrast, CARs of German acquirers with investment banks with low reputation are almost always higher than in the Non-IB-sample. Looking at combined CARs we find no consistent results. 10
  11. 11. A. Acquisitions premiums CAR ( Z ) i (a) 29,24 27,08 60 10,99 8,55 28 18,53*** 0,007 0,006 TAVol i 1,98 1,30 76 1,29 1,08 48 0,22*** 0,000 0,000 TotAss i B. Transaction multiples TAVoli 3,46 0,98 92 1,39 0,85 76 0,13 0,007 0,130 Salesi TAVol i 16,59 11,32 60 10,74 8,05 35 3,27*** 0,028 0,003 EBITDAi *** = significant at the 1%-level. (a) CARi of targts in the [-20;+20] event window Three out of four variables show significant results. German buyers advised by investment banks pay significantly higher acquisition premiums and transaction multiples compared to those without investment banks. No similar results can be shown for German acquirers with investment banks of different reputation (not shown).17 Value creation in M&A-transactions is not only influenced by investment bank participation. To control for other variables, we ran multivariate OLS-regressions (table 8,9 and 10). The control variables analyzed mainly build on the existing literature. The results in table 8 confirm the previous results. Investment bank participation or reputation does not influence CARs received by shareholders of German acquirers. The regression analyzes – considering only investment bank participation (model 1) or reputation (model 3) – does not explain CARs (p-value = 0,705 respectively p-value = 0,839). Also while taking into consideration other variables (model 2 and model 4), investment bank participation or reputation does not have any significant explanatory power (model 2: German buyers with investment banks p- value = 0,239, model 4: German buyers with high reputation investment banks p-value = 0,295). In contrast to investment bank participation or reputation we find a significant positive impact with the relative transaction size (relative transaction volume: p-value = 0,000 (model 2) respectively p-value = 0,014 (model 4)) as well as with the business area of the target (business area of target in new economy: p-value = 0,016 (model 2)). Negative explanatory power we find regarding the absolute size of transaction volume and the dummy variable describing business related transactions (model 2: p-value = 0,046 respectively p-value = 17 Comparing transactions with investment banks with high or low reputation with those advised by no external financial advisor, we find a similar result (not shown). German acquirers with investment banks pay, independent from the reputation of their advisor, higher acquisition premiums and transaction multiples compared to those buyers without investment banks. 11
  12. 12. 0,096). Similar results we obtain while looking at acquisition premiums and transaction multiples (table 9 and 10). In contrast to our previous finding investment bank participation, and reputation, does not have a significant impact on premiums and multiples if other variables are taken into consideration. Significant explanatory power we find regarding the absolute transaction size (table 9, model 3 and 4 and table 10, model 1,2,3 and 4), the cash- asset-ratio of the targets (table 9, model 3 and 4), the country focus (cross-border transactions: table 10, model 4), the existence of a major shareholder (table 10, model 3) and the business focus of the target. In almost every regression analysis, the “new economy-dummy“ is significantly positive. Negative impact on premiums and multiples we find with public targets and (to our surprise) regarding the transaction experience of German buyers (both in table 10, model 3 and 4). In contrast to investment bank participation or reputation, the results of the regression analysis show that the number of investment banks involved has a positive impact on CARs received by the shareholders of German buyers. Table 8 model 4 shows, that CARs of German buyers are higher, if the acquirers use more than one investment bank. The beta-coefficient of the variable “number of investment banks of German acquirer“ is positive and significant (p- value = 0,027). No impact can be shown regarding acquisition premiums or transaction multiples. Table 8: OLS-regression analysis for CARs of German buyers Parameters CARs of German acquirer model 1 model 2 model 3 model 4 German acquirer with investment bank -0,019 -0,100 (0,705) (0,239) German acquirer with high reputation -0,017 0,112 investment bank (0,839) (0,295) 12
  13. 13. Number of investment banks of German 0,261** acquirers (0,027) Acquisition of single assets -0,027 -0,032 (0,738) (0,777) Transaction volume -0,138 -0,246** (0,110) (0,046) Relative transaction volume 0,279*** 0,267*** (0,000) (0,014) Cross-border transactions -0,119 -0,055 (0,122) (0,587) Payment not only cash 0,102 0,140 (0,215) (0,216) Market capitalization German acquirer -0,106 -0,134 (0,219) (0,281) Same (3-digit) industry code of transaction -0,106 -0,177* partners (0,162) (0,096) Number of industry codes target 0,030 0,070 (0,699) (0,518) Business area of target in New Economy 0,197** -0,005 (0,016) (0,965) Prior stake of German acquirer in target (> 5%) 0,004 -0,065 (0,961) (0,527) Target with investment bank -0,058 -0,116 (0,561) (0,339) Target with high reputation investment bank -0,026 0,014 (0,748) (0,901) Transaction experience German acquirer 0,116 0,077 (0,147) (0,468) German acquirer with major shareholder -0,003 -0,117 (>25% of the shares) (0,973) (0,259) (N) 287 177 142 100 Intercept 0,014** 0,023 0,012 -0,022 (0,014) (0,195) (0,102) (0,493) R2 (Adj.) -0,003 0,115 -0,007 0,111 F-value 0,144 2,432*** 0,042 1,775** (0,705) (0,003) (0,839) (0,049) Durbin-Watson-value 1,864 1,877 Table 8 shows the coefficients of the OLS-regressions measuring the impact of various parameters on the CARs of German buyers in the event window [-1;+1]. The corresponding p-values are shown in brackets. * = significant at the 10%-level, ** = significant at the 5%-level, *** = significant at the 1%-level. Table 9: OLS-regression analysis for acquisition premiums paid by German buyers Parameters CAR target TAVol / TotAss model 1 model 2 model 3 model 4 German acquirer with investment bank -0,504 0,079 (0,236) (0,648) German acquirer with high reputation 0,166 -0,144 13
  14. 14. investment bank (0,447) (0,424) Number of investment banks of German 0,029 0,016 acquirers (0,931) (0,920) Transaction volume -0,232 -0,243 0,395*** 0,433** (0,309) (0,374) (0,005) (0,026) Relative transaction volume -0,168 -0,194 0,052 0,135 (0,391) (0,483) (0,683) (0,438) Cross-border transactions 0,048 0,105 0,158 0,217 (0,837) (0,705) (0,278) (0,201) Payment not only cash -0,414* -0,405 (0,065) (0,118) Market capitalization German acquirer -0,150 -0,243 -0,064 0,085 (0,588) (0,374) (0,693) (0,659) Same (3-digit) industry code of transaction 0,261 0,230 0,110 0,130 partners (0,215) (0,339) (0,398) (0,438) Number of industry codes target -0,121 -0,165 -0,150 -0,107 (0,533) (0,468) (0,215) (0,509) Business area of target in New Economy 0,226 0,230 0,273** 0,266* (0,286) (0,333) (0,037) (0,091) Prior stake of German acquirer in target (> 5%) -0,012 -0,067 0,159 0,141 (0,962) (0,818) (0,213) (0,395) Target with investment bank 0,729* 0,329 0,012 -0,085 (0,096) (0,191) (0,938) (0,672) Target with high reputation investment bank -0,137 -0,067 -0,022 -0,028 (0,601) (0,818) (0,883) (0,880) Cash/asset ratio target -0,194 -0,245 0,318** 0,334** (0,334) (0,297) (0,010) (0,043) Publicly listed target -0,178 -0,235 (0,160) (0,183) Transaction experience German acquirer -0,004 -0,033 -0,016 -0,057 (0,984) (0,880) (0,901) (0,726) German acquirer with major shareholder -0,189 -0,169 -0,029 -0,103 (>25% of the shares) (0,342) (0,445) (0,807) (0,525) (N) 39 35 64 45 Intercept 0,047** -0,006 0,059 0,198 (0,044) (0,925) (0,589) (0,389) R2 (Adj.) 0,031 -0,078 0,284 0,207 F-value 1,081 0,847 2,666*** 1,716 (0,422) (0,628) (0,005) (0,102) Durbin-Watson-value 1,872 1,861 2,245 2,165 Table 9 shows the coefficients of the OLS-regressions measuring the impact of various parameters on the acquisition premiums. The corresponding p-values are shown in brackets. * = significant at the 10%-level, ** = significant at the 5%-level, *** = significant at the 1%- level. Table 10: OLS-regression analysis for transaction multiples paid by German buyers Parameter TAVol / Sales TAVol / EBITDA model 1 model 2 model 3 model 4 German acquirer with investment bank 0,061 0,161 (0,696) (0,349) German acquirer with high reputation 0,053 0,035 14
  15. 15. investment bank (0,688) (0,804) Number of investment banks of German 0,022 0,182 acquirers (0,885) (0,217) Transaction volume 0,567*** 0,483*** 0,365** 0,344** (0,000) (0,005) (0,010) (0,044) Relative transaction volume -0,077 -0,003 0,041 0,007 (0,499) (0,981) (0,752) (0,960) Cross-border transactions 0,066 0,137 0,159 0,360** (0,614) (0,356) (0,274) (0,035) Market capitalization German acquirer 0,006 0,120 0,187 0,411** (0,969) (0,467) (0,209) (0,011) Same (3-digit) industry code of transaction 0,172 0,186 0,094 0,106 partners (0,140) (0,196) (0,478) (0,482) Number of industry codes target -0,165 -0,155 -0,154 -0,079 (0,128) (0,270) (0,240) (0,593) Business area of target in New Economy 0,265** 0,326** 0,246* 0,371** (0,027) (0,021) (0,081) (0,042) Prior stake of German acquirer in target (> 5%) 0,089 0,056 0,143 0,040 (0,437) (0,697) (0,254) (0,775) Target with investment bank 0,058 0,057 0,120 -0,054 (0,665) (0,747) (0,425) (0,804) Target with high reputation investment bank -0,030 -0,039 0,167 0,145 (0,816) (0,800) (0,261) (0,395) Cash/asset ration target 0,115 0,048 -0,065 -0,179 (0,285) (0,722) (0,609) (0,288) Publicly listed target -0,154 -0,214 -0,411*** -0,299* (0,175) (0,161) (0,002) (0,092) Transaction experience German acquirer -0,052 -0,079 -0,263* -0,280* (0,654) (0,574) (0,069) (0,055) German acquirer with major shareholder 0,005 -0,021 0,229* 0,258 (>25% of the shares) (0,964) (0,883) (0,086) (0,141) (N) 63 44 51 35 Intercept 0,107 -0,073 1,161* 0,457 (0,763) (0,919) (0,055) (0,654) R2 (Adj.) 0,436 0,439 0,437 0,583 F-value 4,196*** 3,100*** 3,588*** 3,972*** (0,000) (0,005) (0,001) (0,003) Durbin-Watson-value 2,033 2,216 1,894 2,329 Table 10 shows the coefficients of the OLS-regressions measuring the impact of various parameters on the transaction multiples. The corsponding p-values are shown in brackets. * = significant at the 10%-level, ** = significant at the 5%-level, *** = significant at the 1%- level. Besides CARs and purchase prices, investment bank participation might be advantageous to German acquirers if the M&A-advisors are able to influence the time to completion of a transaction.18 A shorter time to completion reduces confusion surrounding a transaction (e.g. uncertainty of staff, clients or suppliers) and therefore transaction costs (e.g. in the form of 18 It would be also interesting to investigate whether investment bank participation or reputation has an impact on the total duration of transaction execution. As public information on this period of time is not available, we cannot analyze this period. 15
  16. 16. lost customers or key staff). Table 11 shows the time to completion of the transactions in our samples. The average time to completion in the IB-sample is 102 days, whereas it is 42 days in the Non-IB-sample. The period between transaction announcement and completion for German buyers with investment banks is more than twice as long as the corresponding period in the Non-IB-sample. Table 11: Time to completion IB-Sample Non-IB-Sample – 151 140 140 120 120 102 100 100 80 80 Tage Tage 66 68 60 60 44 40 40 31 20 20 0 0 25-99 101-499 >500 25-99 101-499 >500 Transaktionsvolumen in Mio. EUR Transaktionsvolumen in Mio. EUR One important factor influencing time to completion is the transaction size: The average time to completion increases with higher transaction volumes. Looking at different transaction size sub-samples, we still find, that time to completion is significantly higher in the IB-sample.19 To control for other variables influencing time to completion, we ran multivariate OLS- regressions. The results shown in table 12 do not support our previous findings. Table 12: OLS-Regression analysis for the time to completion Parameters Time to completion model 1 model 2 German acquirer with investment bank 0,081 (0,290) German acquirer with high reputation investment bank 0,040 (0,662) 19 Transaction volume between 25 and 99 Mio. EUR: MWU p-value < 0,000, transaction volume between 100 and 499 Mio. EUR: MWU p-value < 0,000, transaction volume greater than 500 Mio. EUR: MWU p-value = 0,088. 16
  17. 17. Number of investment banks of German acquirers 0,329*** (0,002) Acquisition of single assets 0,080 0,057 (0,294) (0,582) Transaction volume 0,159** 0,109 (0,042) (0,313) Relative transaction volume 0,097 0,041 (0,157) (0,654) Cross-border transactions -0,098 -0,049 (0,156) (0,586) Payment nor only in cash 0,142* 0,119 (0,062) (0,229) Market capitalization German acquirer 0,063 -0,035 (0,419) (0,747) Publicly listed target 0,074 -0,115 (0,361) (0,308) Same (3-digit) industry code of transaction partners 0,048 0,017 (0,484) (0,852) Number of industry codes target -0,035 0,027 (0,618) (0,775) Business area of target in New Economy -0,116 -0,111 (0,121) (0,274) Prior stake of German acquirer in target (> 5%) 0,098 0,187** (0,159) (0,043) Target with investment bank 0,110 0,125 (0,182) (0,208) Target with high reputation investment bank -0,061 -0,010 (0,412) (0,921) Transaction experience German acquirer 0,126* 0,148 (0,080) (0,114) (N) 212 124 Intercept 4,109* -3,298 (0,071) (0,466) R2 (Adj.) 0,117 0,161 F-value 2,856*** 2,480*** (0,000) (0,003) Durbin-Watson-value 2,014 2,130 Table 10 shows the coefficients of the OLS-regressions measuring the impact of various parameters on the time to completion. The corresponding p-values are shown in brackets. * = significant at the 10%-level, ** = significant at the 5%-level, *** = significant at the 1%- level. After controlling for other variables, investment bank participation does not have a significant impact on time to completion (table 12, model 1: German acquirer with investment bank: p- value = 0,290, model 2: German acquirer with high reputation investment bank: p-value = 0,662). Positive impact we find regarding the transaction volume (model 1: p-value = 0,042), the method of payment (payment not only cash, model 1: p-value = 0,062), prior stake of German acquirer in target (model 2: p-value = 0,043) and regarding transaction experience of German buyers (model 1: p-value = 0,080). 17
  18. 18. In contrast to investment banks participation or reputation, again the number of investment banks involved does have a significant impact on the duration between transaction announcement and completion. The corresponding beta-coefficient in table 12, model 2 (“number of investment banks of German acquirer“) equals 0,329 (p-value = 0,002). We already showed that investment bank participation nor reputation does have an impact on CARs, purchase prices or time to completion. But do German buyers benefit from investment bank participation or reputation in the mid-term? Table 13 summarizes the results: The mid- term acquisition performance of the analyzed buyers with and without investment banks do not differ significantly. Also investment bank reputation has no impact (table 14). Table 13: Mid-term acquisition performance of German buyers with and without investment banks IB-sample Non-IB-sample Sub-samples Aver- Median (N) Aver- Median (N) difference t-test MWU age age medians p-val. p-value 125 trading days 4,62 -1,52 61 1,14 -9,41 53 7,89 0,371 0,328 250 trading days 2,81 -8,04 61 -1,54 -11,58 53 3,54 0,367 0,472 Table 14: Mid-term acquisition performance of German buyers with investment banks with different reputation IB with high IB with low reputation Reputation Sub-samples Aver- Median (N) Aver- Median (N) difference t-test MWU age age medians p-val. p-value 125 trading days -3,19 -11,88 15 7,56 0,00 46 -11,88 0,231 0,319 250 trading days -10,36 -7,11 15 7,47 -7,53 46 0,42 0,135 0,433 4. Summary and conclusion In this paper, we analyzed four research questions. We investigated whether investment bank participation and/or reputation has an impact on (short-term) CARs of German buyers, on purchase prices and on time to completion. Further we looked at the mid-term acquisition performance of German acquirers. The results confirm the existing (US-focused) empirical literature. Investment bank participation and/or reputation does not have a significant impact 18
  19. 19. on abnormal cumulative returns received by shareholders of German acquirers. The mid-term acquisition performance of German acquirers is also not influenced by investment bank participation nor reputation. Also transactions with (short-term) CARs do not show positive mid-term acquisition performances more often if investment banks are involved. Similar results we find regarding acquisition premiums and transaction multiples. While looking at investment bank participation alone, we find that German acquirers pay higher acquisition premiums and transaction multiples in transactions advised by investment banks. However this results can not be confirmed taking into consideration other variables in the regression analyzes. In contrast to investment bank participation we find, that other deal-characteristics, like the transaction volume or the business focus of the target do have significant explanatory power in explaining CARs and purchase prices. German buyers do not pay higher premiums and multiples if they use investment banks, but if they proceed in bigger transactions or if they acquire targets in business areas with (potentially) greater revenue potentials. In this aspect, this study confirms the results obtained by Hunter and Walker (1990) or Servaes and Zenner (1996) who can not find a significant relations-ship between investment bank participation and acquisition premiums. In contrast to Michel et al. (1991), McLaughlin (1992) or Rau (2000) we can not show, that German buyers advised by investment banks with higher reputation pay higher acquisition premiums. German acquirers pay similar acquistion premiums and transaction multiples independent from the reputation of the respective M&A- advisors. A different result we find regarding the number of investment banks involved. Shareholders of German acquirers do benefit if its management mandates more than one investment bank. This results confirms the results of Hunter and Jagtiani (2000). The number of investment banks does not only influence CARs, but also the duration between transaction announcement and completion. The shareholders of German acquirers benefit if its management uses more than one M&A-advisor. At the same time they „suffer“ from longer time to completions. A possible explanation for the positive impact of more than one investment banks could be the combination of different product- and transaction-expertise of the various investment banks involved that leads to better results. Also competition among the advisors for potential add-on mandates could play an important factor. A reason for the increased time to completion might be that the investment banks need more time to coordinate their advisory services. 19
  20. 20. As the main results of this study we find that investment bank participation and reputation does have a very limited impact on value creation in M&A-transactions of German acquirers. In this aspect, the management of German acquirers can not rely on the investment banks involved. Instead the ultimate responsibility for value creation in M&A-transactions rests with the management. Bibliography 20
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